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Guiding the Interactive Exploration of Metabolic Pathway Interconnections
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. (ISOVIS)ORCID iD: 0000-0001-6745-4398
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. (ISOVIS)ORCID iD: 0000-0002-0519-2537
2012 (English)In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 11, no 2, p. 136-150Article in journal (Refereed) Published
Abstract [en]

Approaches to investigate biological processes have been of strong interest in the past few years and are thefocus of several research areas, especially Systems Biology. Biochemical networks as representations ofprocesses are very important for a comprehensive understanding of living beings. Drawings of these networksare often visually overloaded and do not scale. A common solution to deal with this complexity is to divide thecomplete network, for example, the metabolism, into a large set of single pathways that are hierarchicallystructured. If those pathways are visualized, this strategy generates additional navigation and explorationproblems as the user loses the context within the complete network.

In this article, we present a general solution to this problem of visualizing interconnected pathways anddiscuss it in context of biochemical networks. Our new visualization approach supports the analyst in obtainingan overview to related pathways if they are working within a particular pathway of interest. By usingglyphs, brushing, and topological information of the related pathways, our interactive visualization is ableto intuitively guide the exploration and navigation process, and thus the analysis processes too. To deal withreal data and current networks, our tool has been implemented as a plugin for the VANTED system.

Place, publisher, year, edition, pages
SAGE Publications , 2012. Vol. 11, no 2, p. 136-150
Keywords [en]
network visualization, biochemical networks, navigation, glyphs
National Category
Computer Sciences Bioinformatics (Computational Biology)
Research subject
Computer and Information Sciences Computer Science, Computer Science; Computer and Information Sciences Computer Science; Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-13919DOI: 10.1177/1473871611405677Scopus ID: 2-s2.0-84871727664OAI: oai:DiVA.org:lnu-13919DiVA, id: diva2:437185
Available from: 2011-08-26 Created: 2011-08-26 Last updated: 2018-01-12Bibliographically approved

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Jusufi, IlirKerren, Andreas

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